Articles sponsored by established companies in the Sensors industry.
Filtering algorithms play an important role in detecting and excluding outliers from travel time data. The SMATS algorithm has been designed and tested to work with both low and high sample sizes as well as arterial and freeway travel time data.
This case study by SMATS looks at how integrated crowdsourced traffic data can allow the City of St. Petersburg to monitor and capture on-demand travel time data for any road segment in the City for any time and date.
For this case study, SMATS partners with Salander Technology Services creates a smart work zone system with TrafficXHub™ sensors.
In this case study, Collier County Traffic Operation chooses SMATS Traffic Solutions’ data analytics platform, iNode™, to easily monitor and analyze travel time in real-time.
For this case study, the city of Ottawa uses SMATA INODE™ crowdsourced traffic data analytics in various different traffic products.
In this case study, SMATS sensors are deployed at Parliament Hill during Canada Day to measure lineup wait time in real-time.
For this case study, SMATS Bluetooth and WIFI sensors are utilized in the estimation of transit passengers' origin-destination.
Travel Time Reliability (TTR) measures a variety of components, including Travel-Time Index, Buffer Index, and Planning Time Index.
The technological era is among us, and to stay competitive it is crucial to consistently utilize new technology and improve outdated systems - discover how these 8 ports and rail yards are cracking congestion.
With population growth and the expansion of roads, traffic congestion has become a significant problem worldwide. Crowdsourced traffic data is a new way of capturing traffic congestion data.